The relationship between complement C3 expression and the MUC5B genotype in pulmonary fibrosis.

The common gain-of-function MUC5B promoter variant ( rs35705950 ) is the strongest risk factor for the development of idiopathic pulmonary fibrosis (IPF). While the role of complement in IPF is controversial, both MUC5B and the complement system play a role in lung host defense. The aim of this study was to evaluate the relationship between complement component 3 (C3) and MUC5B in patients with IPF and in bleomycin-induced lung injury in mice. To do this, we evaluated C3 gene expression in whole lung tissue from 300 subjects with IPF and 175 healthy controls. Expression of C3 was higher in IPF than healthy controls {1.40-fold increase [95% confidence interval (CI) 1.31-1.50]; P < 0.0001} and even greater among IPF subjects with the highest-risk IPF MUC5B promoter genotype [TT vs. GG = 1.59-fold (95% CI 1.15-2.20); P < 0.05; TT vs. GT = 1.66-fold (95% CI 1.20-2.30); P < 0.05]. Among subjects with IPF, C3 expression was significantly higher in the lung tissue without microscopic honeycombing than in the lung tissue with microscopic honeycombing [1.40-fold increase (95% CI 1.23- 1.59); P < 0.01]. In mice, while bleomycin exposure increased Muc5b protein expression, C3-deficient mice were protected from bleomycin-induced lung injury. In aggregate, our findings indicate that the MUC5B promoter variant is associated with higher C3 expression and suggest that the complement system may contribute to the pathogenesis of IPF.

Role of mucins in lung homeostasis: regulated expression and biosynthesis in health and disease.

In humans and mice, the first line of innate defense against inhaled pathogens and particles in the respiratory tract is airway mucus. The primary solid components of the mucus layer are the mucins MUC5AC and MUC5B, polymeric glycoproteins whose changes in abundance and structure can dramatically affect airway defense. Accordingly, MUC5AC/Muc5ac and MUC5B/Muc5b are tightly regulated at a transcriptional level by tissue-specific transcription factors in homeostasis and in response to injurious and inflammatory triggers. In addition to modulated levels of mucin gene transcription, translational and post-translational biosynthetic processes also exert significant influence upon mucin function. Mucins are massive macromolecules with numerous functional domains that contribute to their structural composition and biophysical properties. Single MUC5AC and MUC5B apoproteins have molecular masses of >400 kDa, and von Willebrand factor D-like as well as other cysteine-rich domain segments contribute to mucin polymerization and flexibility, thus increasing apoprotein length and complexity. Additional domains serve as sites for O-glycosylation, which increase further mucin mass several-fold. Glycosylation is a defining process for mucins that is specific with respect to additions of glycans to mucin apoprotein backbones, and glycan additions influence the physical properties of the mucins via structural modifications as well as charge interactions. Ultimately, through their tight regulation and complex assembly, airway mucins follow the biological rule of 'form fits function' in that their structural organization influences their role in lung homeostatic mechanisms.

Control of lung defence by mucins and macrophages: ancient defence mechanisms with modern functions.

Owing to the need to balance the requirement for efficient respiration in the face of tremendous levels of exposure to endogenous and environmental challenges, it is crucial for the lungs to maintain a sustainable defence that minimises damage caused by this exposure and the detrimental effects of inflammation to delicate gas exchange surfaces. Accordingly, epithelial and macrophage defences constitute essential first and second lines of protection that prevent the accumulation of potentially harmful agents in the lungs, and under homeostatic conditions do so effectively without inducing inflammation. Though epithelial and macrophage-mediated defences are seemingly distinct, recent data show that they are linked through their shared reliance on airway mucins, in particular the polymeric mucin MUC5B. This review highlights our understanding of novel mechanisms that link mucus and macrophage defences. We discuss the roles of phagocytosis and the effects of factors contained within mucus on phagocytosis, as well as newly identified roles for mucin glycoproteins in the direct regulation of leukocyte functions. The emergence of this nascent field of glycoimmunobiology sets forth a new paradigm for considering how homeostasis is maintained under healthy conditions and how it is restored in disease.

An open source knowledge graph ecosystem for the life sciences.

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

Knowledge-Driven Mechanistic Enrichment of the Preeclampsia Ignorome.

Preeclampsia is a leading cause of maternal and fetal morbidity and mortality. Currently, the only definitive treatment of preeclampsia is delivery of the placenta, which is central to the pathogenesis of the disease. Transcriptional profiling of human placenta from pregnancies complicated by preeclampsia has been extensively performed to identify differentially expressed genes (DEGs). The decisions to investigate DEGs experimentally are biased by many factors, causing many DEGs to remain uninvestigated. A set of DEGs which are associated with a disease experimentally, but which have no known association to the disease in the literature are known as the ignorome. Preeclampsia has an extensive body of scientific literature, a large pool of DEG data, and only one definitive treatment. Tools facilitating knowledge-based analyses, which are capable of combining disparate data from many sources in order to suggest underlying mechanisms of action, may be a valuable resource to support discovery and improve our understanding of this disease. In this work we demonstrate how a biomedical knowledge graph (KG) can be used to identify novel preeclampsia molecular mechanisms. Existing open source biomedical resources and publicly available high-throughput transcriptional profiling data were used to identify and annotate the function of currently uninvestigated preeclampsia-associated DEGs. Experimentally investigated genes associated with preeclampsia were identified from PubMed abstracts using text-mining methodologies. The relative complement of the text-mined- and meta-analysis-derived lists were identified as the uninvestigated preeclampsia-associated DEGs (n=445), i.e., the preeclampsia ignorome. Using the KG to investigate relevant DEGs revealed 53 novel clinically relevant and biologically actionable mechanistic associations.

Ontologizing health systems data at scale: making translational discovery a reality.

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68-99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

Siglec-6 Signaling Uses Src Kinase Tyrosine Phosphorylation and SHP-2 Recruitment.

Preeclampsia is a pregnancy-specific disorder involving placental abnormalities. Elevated placental Sialic acid immunoglobulin-like lectin (Siglec)-6 expression has been correlated with preeclampsia. Siglec-6 is a transmembrane receptor, expressed predominantly by the trophoblast cells in the human placenta. It interacts with sialyl glycans such as sialyl-TN glycans as well as binds leptin. Siglec-6 overexpression has been shown to influence proliferation, apoptosis, and invasion in the trophoblast (BeWo) cell model. However, there is no direct evidence that Siglec-6 plays a role in preeclampsia pathogenesis and its signaling potential is still largely unexplored. Siglec-6 contains an immunoreceptor tyrosine-based inhibitory motif (ITIM) and an ITIM-like motif in its cytoplasmic tail suggesting a signaling function. Site-directed mutagenesis and transfection were employed to create a series of Siglec-6 expressing HTR-8/SVneo trophoblastic cell lines with mutations in specific functional residues to explore the signaling potential of Siglec-6. Co-immunoprecipitation and inhibitory assays were utilized to investigate the association of Src-kinases and SH-2 domain-containing phosphatases with Siglec-6. In this study, we show that Siglec-6 is phosphorylated at ITIM and ITIM-like domains by Src family kinases. Phosphorylation of both ITIM and ITIM-like motifs is essential for the recruitment of phosphatases like Src homology region 2 containing protein tyrosine phosphatase 2 (SHP-2), which has downstream signaling capabilities. These findings suggest Siglec-6 as a signaling molecule in human trophoblasts. Further investigation is warranted to determine which signaling pathways are activated downstream to SHP-2 recruitment and how overexpression of Siglec-6 in preeclamptic placentas impacts pathogenesis.

Alterations in rat fetal morphology following abuse patterns of toluene exposure.

Toluene is a commonly abused organic solvent. Inhalant abusers are increasingly women in their prime childbearing years. Children born to mothers who abused solvents during pregnancy may exhibit characteristics of a "fetal solvent syndrome" which may include dysmorphic features. This study examined the teratological effects of an abuse pattern of binge toluene exposure during gestation on skeletal and soft tissue abnormalities, body weight, and body size in fetal rats. Pregnant Sprague-Dawley rats were exposed for 30 min, twice daily, from gestational day (GD) 8 through GD20 to either air (0 ppm), 8000 ppm, 12,000 ppm, or 16,000 ppm toluene. Two-thirds of each litter was prepared for skeletal examination using Alizarin Red S staining while the remaining third of each litter was fixed in Bouin's solution for Wilson's soft tissue evaluation. Exposure to toluene at all levels significantly reduced growth, including decreases in placental weight, fetal weight, and crown-rump length. In addition, numerous gross morphological anomalies were observed such as short or missing digits and missing limbs. Skeletal examination revealed that ossification of the extremities was significantly reduced as a result of toluene exposure at all levels. Specific skeletal defects included misshapen scapula, missing and supernumerary vertebrae and ribs, and fused digits. Soft tissue anomalies were also observed at all toluene levels and there was a dose-dependent increase in the number of anomalies which included cryptorchidism, displaced abdominal organs, gastromegaly, distended/hypoplastic bladder, and delayed cardiac development, among others. These results indicate that animals exposed prenatally to levels and patterns of toluene typical of inhalant abuse are at increased risk for skeletal and soft tissue abnormalities.

Murine trophoblast-derived and pregnancy-associated exosome-enriched extracellular vesicle microRNAs: Implications for placenta driven effects on maternal physiology.

The role of extracellular vesicles (EVs), specifically exosomes, in intercellular communication likely plays a key role in placental orchestration of pregnancy and maternal immune sensing of the fetus. While murine models are powerful tools to study pregnancy and maternal-fetal immune interactions, in contrast to human placental exosomes, the content of murine placental and pregnancy exosomes remains largely understudied. Using a recently developed in vitro culture technique, murine trophoblast stem cells derived from B6 mice were differentiated into syncytial-like cells. EVs from the conditioned media, as well as from pregnant and non-pregnant sera, were enriched for exosomes. The RNA composition of these murine trophoblast-derived and pregnancy-associated exosome-enriched-EVs (ExoE-EVs) was determined using RNA-sequencing analysis and expression levels confirmed by qRT-PCR. Differentially abundant miRNAs were detected in syncytial differentiated ExoE-EVs, particularly from the X chromosome cluster (mmu-miR-322-3p, mmu-miR-322-5p, mmu-miR-503-5p, mmu-miR-542-3p, and mmu-miR-450a-5p). These were confirmed to be increased in pregnant mouse sera ExoE-EVs by qRT-PCR analysis. Interestingly, fifteen miRNAs were only present within the pregnancy-derived ExoE-EVs compared to non-pregnant controls. Mmu-miR-292-3p and mmu-miR-183-5p were noted to be some of the most abundant miRNAs in syncytial ExoE-EVs and were also present at higher levels in pregnant versus non-pregnant sera ExoE-EVs. The bioinformatics tool, MultiMir, was employed to query publicly available databases of predicted miRNA-target interactions. This analysis reveals that the X-chromosome miRNAs are predicted to target ubiquitin-mediated proteolysis and intracellular signaling pathways. Knowing the cargo of placental and pregnancy-specific ExoE-EVs as well as the predicted biological targets informs studies using murine models to examine not only maternal-fetal immune interactions but also the physiologic consequences of placental-maternal communication.

Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery.

Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2923 commonly used laboratory tests with HPO terms. Using these annotations, our software assesses laboratory test results and converts each result into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows readily available laboratory tests in EHR to be reused for deep phenotyping and exploits the hierarchical structure of HPO to integrate distinct tests that have comparable medical interpretations for association studies.

Modulation of Lung Epithelial Cell Function Using Conditional and Inducible Transgenic Approaches.

In the lungs, the epithelium is a first line of innate defense. In acute settings, such as infection or particulate exposure, the epithelium is protective. Protection is conferred by the epithelium's role as a physical barrier and by its ability to synthesize proteins that promote defense directly through physical interactions (e.g., mucins and anti-microbial peptides) and indirectly through the production of proteins that regulate inflammation (e.g., cytokines and chemokines). Despite its importance as a first line of host defense, the epithelium is also a significant target and an effector in lung pathologies. Accordingly, to determine the significance and biological mechanisms of genes involved in pulmonary defense, it is important to be able to interrogate the lung epithelium. In mice, this presents challenges related to the cellular location and timing of interventions. Effective genetic strategies for targeting the lung epithelium using tissue-/cell-specific and inducible control have been developed over the past decade. Methods for spatiotemporal targeting of gene expression are described here.

OWL-NETS: Transforming OWL Representations for Improved Network Inference.

Our knowledge of the biological mechanisms underlying complex human disease is largely incomplete. While Semantic Web technologies, such as the Web Ontology Language (OWL), provide powerful techniques for representing existing knowledge, well-established OWL reasoners are unable to account for missing or uncertain knowledge. The application of inductive inference methods, like machine learning and network inference are vital for extending our current knowledge. Therefore, robust methods which facilitate inductive inference on rich OWL-encoded knowledge are needed. Here, we propose OWL-NETS (NEtwork Transformation for Statistical learning), a novel computational method that reversibly abstracts OWL-encoded biomedical knowledge into a network representation tailored for network inference. Using several examples built with the Open Biomedical Ontologies, we show that OWL-NETS can leverage existing ontology-based knowledge representations and network inference methods to generate novel, biologically-relevant hypotheses. Further, the lossless transformation of OWL-NETS allows for seamless integration of inferred edges back into the original knowledge base, extending its coverage and completeness.

Maternal obesity during lactation may protect offspring from high fat diet-induced metabolic dysfunction.

BACKGROUND/OBJECTIVES: The current obesity epidemic has spurred exploration of the developmental origin of adult heath and disease. A mother's dietary choices and health can affect both the early wellbeing and lifelong disease-risk of the offspring. SUBJECTS/METHODS: To determine if changes in the mother's diet and adiposity have long-term effects on the baby's metabolism, independently from a prenatal insult, we utilized a mouse model of diet-induced-obesity and cross-fostering. All pups were born to lean dams fed a low fat diet but were fostered onto lean or obese dams fed a high fat diet. This study design allowed us to discern the effects of a poor diet from those of mother's adiposity and metabolism. The weaned offspring were placed on a high fat diet to test their metabolic function. RESULTS: In this feeding challenge, all male (but not female) offspring developed metabolic dysfunction. We saw increased weight gain in the pups nursed on an obesity-resistant dam fed a high fat diet, and increased pathogenesis including liver steatosis and adipose tissue inflammation, when compared to pups nursed on either obesity-prone dams on a high fat diet or lean dams on a low fat diet. CONCLUSION: Exposure to maternal over-nutrition, through the milk, is sufficient to shape offspring health outcomes in a sex- and organ-specific manner, and milk from a mother who is obesity-prone may partially protect the offspring from the insult of a poor diet.

Dynamics and molecular determinants of cytoplasmic lipid droplet clustering and dispersion.

Perilipin-1 (Plin1), a prominent cytoplasmic lipid droplet (CLD) binding phosphoprotein and key physiological regulator of triglyceride storage and lipolysis in adipocytes, is thought to regulate the fragmentation and dispersion of CLD that occurs in response to ß-adrenergic activation of adenylate cyclase. Here we investigate the dynamics and molecular determinants of these processes using cell lines stably expressing recombinant forms of Plin1 and/or other members of the perilipin family. Plin1 and a C-terminal CLD-binding fragment of Plin1 (Plin1CT) induced formation of single dense CLD clusters near the microtubule organizing center, whereas neither an N-terminal CLD-binding fragment of Plin1, nor Plin2 or Plin3 induced clustering. Clustered CLD coated by Plin1, or Plin1CT, dispersed in response to isoproterenol, or other agents that activate adenylate cyclase, in a process inhibited by the protein kinase A inhibitor, H89, and blocked by microtubule disruption. Isoproterenol-stimulated phosphorylation of CLD-associated Plin1 on serine 492 preceded their dispersion, and live cell imaging showed that cluster dispersion involved initial fragmentation of tight clusters into multiple smaller clusters, which then fragmented into well-dispersed individual CLD. siRNA knockdown of the cortical actin binding protein, moesin, induced disaggregation of tight clusters into multiple smaller clusters, and inhibited the reaggregation of dispersed CLD into tight clusters. Together these data suggest that the clustering and dispersion processes involve a complex orchestration of phosphorylation-dependent, microtubule-dependent and independent, and microfilament dependent steps.

The discovery of a reciprocal relationship between tyrosine-kinase signaling and cullin neddylation.

While neddylation is known to activate cullin (CUL)-RING ubiquitin ligases (CRLs), its role in regulating T cell signaling is poorly understood. Using the investigational NEDD8 activating enzyme (NAE) inhibitor, MLN4924, we found that neddylation negatively regulates T cell receptor (TCR) signaling, as its inhibition increases IL-2 production, T cell proliferation and Treg development in vitro. We also discovered that loss of CUL neddylation occurs upon TCR signaling, and CRLs negatively regulate IL-2 production. Additionally, we found that tyrosine kinase signaling leads to CUL deneddylation in multiple cell types. These studies indicate that CUL neddylation is a global regulatory mechanism for tyrosine kinase signaling.

Pregnancy amelioration of arthritis in SKG mice corresponds with alterations in serum amyloid A3 levels.

OBJECTIVES: Pregnancy leads to rheumatoid arthritis remission in humans. The objective of this study was to determine if the SKG mouse could serve as a model for pregnancy-associated inflammatory arthritis amelioration. In addition, the maternal peripheral blood mononuclear cell (PBMC) transcriptome was assessed to define a biomarker associated with remission. METHODS: Cohorts of zymosan-treated pregnant SKG mice and controls were monitored for arthritis progression. Microarray analysis evaluated alterations in gene expression in maternal PBMCs at embryonic day 14.5 (E14.5) between arthritic and pregnancy-remitted mice. A selected target, serum amyloid A3 (SAA3), was further investigated using quantitative reverse transcriptase PCR (qRT-PCR) and an enzyme-linked immunosorbent assay (ELISA). RESULTS: Pregnancy resulted in complete or partial remission in the majority of the zymosan-treated SKG mice. Twenty-seven transcripts were differentially expressed in the PBMCs between arthritic and pregnancy-remitted mice. Expression and plasma SAA3 levels decreased with pregnancy-induced arthritis amelioration and plasma SAA3 levels correlated with arthritis severity. CONCLUSIONS: These results establish the SKG mouse as a model system to study pregnancy-induced amelioration of arthritis. These studies also establish SAA3 as a biomarker of arthritis amelioration in SKG mice. This model can be used to elucidate the molecular and cellular mechanisms underlying the impact of pregnancy on the maternal immune system that results in arthritis amelioration.