Characterization of resistance to halogenated aromatic hydrocarbons in a population of Fundulus heteroclitus from a marine superfund site

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 1999New Bedford Harbor (NBH), MA, is contaminated with halogenated aromatic hydrocarbons HAH including some potent aryl hydrocarbon receptor AhR agonists. To determine if Fundulus heterocitus from NBH have developed resistance to HAll, we examined the inducibility of cytochrome P4501A1 CYP1A1 in fish from NBH and Scorton Creek SC, reference site. Despite higher PCB concentrations in NBH than in SC fish - -1 500-fold - CYP1A1 expression, in most tissues, was not higher in NBH fish than in SC fish. Glutathione S-transferase GST and UDP-glucuronosyltransferase UGT activities were higher in NBH fish than in SC fish, but only when fish were collected during different seasons. GST activity was higher in the intestines ofNBH fish than in any other tissue. 2,3,7,8-TetrachlorodibenzoftiranTCDF induced CYP1A1 expression, in all tissues examined, in SC fish. In contrast, NBH fish showed little CYP1A1 induction by any measure, in any tissue. Hepatic GST activity was induced only in male NBH fish. Hepatic UGT activity showed no relationship to treatment in fish from either site. 2,3,7,8-Tetrachlorodibenzo-p-dioxin TCDD and J3-naphthoflavone BNF induced CYP1A1 activity to the same level in primary cultures ofhepatocytes from either SC orNBH fish. However, hepatocytes from NBH fish were 14-fold less sensitive to TCDD and 3-fold less sensitive to BNF than hepatocytes from SC fish. To examine the heritability ofresistance, NBH and SC F1 fish were treated with 3HTCDD or BNF. 3H-TCDD induced CYP1A1 expression only in SC F1 fish. BNF induced CYP1A1 expression in both SC and NBH F1 fish. There was no significant difference in hepatic 3H-TCDD concentrations between SC and NBH F1 fish. Hepatic AhR content, as measured by photoaffinity labeling with 125I-N3Br2DD, was lower in NBH fish than in SC fish and lower in males than in females. After 90 days in captivity, the sex difference persisted, but the site difference did not. TCDF induced hepatic AIIR content in NBH F1 fish. These results indicate that NBH Fundulus have developed a pre-translational, systemic, heritable resistance to HAHs. These findings suggest that an alteration in the AIIR pathway is responsible for this resistance; this is the subject of continuing research.This work was supported by a National Science Foundation Graduate Fellowship Program and by a National Institute of Environmental Health and Safety grant P42 ES073 81 Superfund Basic Research Program at Boston Universit

Conference report: Biocuration 2021 Virtual Conference.

The International Society for Biocuration (ISB) aims to promote the field of biocuration and provide a community forum for information exchange and networking. Over the past 14 years, the ISB has hosted annual international conferences, entirely dedicated to the field of biocuration, that rotate between regions across the world. These meetings bring together biocurators from various roles, including database curators, bioinformaticians, ontology developers and students. Due to the ongoing global pandemic, the 14th Annual ISB Biocuration Conference (ISB2021) was held virtually in the form of four sessions and one workshop over the course of the year. Each of the four virtual sessions included panel discussions covering (i) The Future of Biocuration, (ii) Career paths and projections in Biocuration, (iii) Addressing Implicit or Unconscious Bias: Equity, Diversity and Inclusion and (iv) Strategic planning. Here we report on highlights from the virtual conference and share some of the ideas and future goals of the ISB. Database URL:https://www.biocuration.org/14th-annual-biocuration-conference-virtual/

Inferential considerations for low-count RNA-seq transcripts: a case study on the dominant prairie grass Andropogon gerardii

Citation: Raithel, S., Johnson, L., Galliart, M., Brown, S., Shelton, J., Herndon, N., & Bello, N. M. (2016). Inferential considerations for low-count RNA-seq transcripts: a case study on the dominant prairie grass Andropogon gerardii. Bmc Genomics, 17, 16. doi:10.1186/s12864-016-2442-7Background: Differential expression (DE) analysis of RNA-seq data still poses inferential challenges, such as handling of transcripts characterized by low expression levels. In this study, we use a plasmode-based approach to assess the relative performance of alternative inferential strategies on RNA-seq transcripts, with special emphasis on transcripts characterized by a small number of read counts, so-called low-count transcripts, as motivated by an ecological application in prairie grasses. Big bluestem (Andropogon gerardii) is a wide-ranging dominant prairie grass of ecological and agricultural importance to the US Midwest while edaphic subspecies sand bluestem (A. gerardii ssp. Hallii) grows exclusively on sand dunes. Relative to big bluestem, sand bluestem exhibits qualitative phenotypic divergence consistent with enhanced drought tolerance, plausibly associated with transcripts of low expression levels. Our dataset consists of RNA-seq read counts for 25,582 transcripts (60 % of which are classified as low-count) collected from leaf tissue of individual plants of big bluestem (n = 4) and sand bluestem (n = 4). Focused on low-count transcripts, we compare alternative ad-hoc data filtering techniques commonly used in RNA-seq pipelines and assess the inferential performance of recently developed statistical methods for DE analysis, namely DESeq2 and edgeR robust. These methods attempt to overcome the inherently noisy behavior of low-count transcripts by either shrinkage or differential weighting of observations, respectively. Results: Both DE methods seemed to properly control family-wise type 1 error on low-count transcripts, whereas edgeR robust showed greater power and DESeq2 showed greater precision and accuracy. However, specification of the degree of freedom parameter under edgeR robust had a non-trivial impact on inference and should be handled carefully. When properly specified, both DE methods showed overall promising inferential performance on low-count transcripts, suggesting that ad-hoc data filtering steps at arbitrary expression thresholds may be unnecessary. A note of caution is in order regarding the approximate nature of DE tests under both methods. Conclusions: Practical recommendations for DE inference are provided when low-count RNA-seq transcripts are of interest, as is the case in the comparison of subspecies of bluestem grasses. Insights from this study may also be relevant to other applications focused on transcripts of low expression levels

Disease Ontology: improving and unifying disease annotations across species.

Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontologies), making comparisons and inferences difficult. A unified disease ontology is required that connects data annotated using diverse disease terminologies, and in which the terminology relationships are continuously maintained. The Mouse Genome Database (MGD, http://www.informatics.jax.org), Rat Genome Database (RGD, http://rgd.mcw.edu) and Disease Ontology (DO, http://www.disease-ontology.org) projects are collaborating to augment DO, aligning and incorporating disease terms used by MGD and RGD, and improving DO as a tool for unifying disease annotations across species. Coordinated assessment of MGD\u27s and RGD\u27s disease term annotations identified new terms that enhance DO\u27s representation of human diseases. Expansion of DO term content and cross-references to clinical vocabularies (e.g. OMIM, ORDO, MeSH) has enriched the DO\u27s domain coverage and utility for annotating many types of data generated from experimental and clinical investigations. The extension of anatomy-based DO classification structure of disease improves accessibility of terms and facilitates application of DO for computational research. A consistent representation of disease associations across data types from cellular to whole organism, generated from clinical and model organism studies, will promote the integration, mining and comparative analysis of these data. The coordinated enrichment of the DO and adoption of DO by MGD and RGD demonstrates DO\u27s usability across human data, MGD, RGD and the rest of the model organism database community. Dis Model Mech 2018 Mar 12;11(3):dmm032839

A living cell quartz crystal microbalance biosensor for continuous monitoring of cytotoxic responses of macrophages to single-walled carbon nanotubes

<p>Abstract</p> <p>Background</p> <p>Numerous engineered nanomaterials (ENMs) exist and new ENMs are being developed. A challenge to nanotoxicology and environmental health and safety is evaluating toxicity of ENMs before they become widely utilized. Cellular assays remain the predominant test platform yet these methods are limited by using discrete time endpoints and reliance on organic dyes, vulnerable to interference from ENMs. Label-free, continuous, rapid response systems with biologically meaningful endpoints are needed. We have developed a device to detect and monitor in real time responses of living cells to ENMs. The device, a living cell quartz crystal microbalance biosensor (QCMB), uses macrophages adherent to a quartz crystal. The communal response of macrophages to treatments is monitored continuously as changes in crystal oscillation frequency (Δf). We report the ability of this QCMB to distinguish benign from toxic exposures and reveal unique kinetic information about cellular responses to varying doses of single-walled carbon nanotubes (SWCNTs).</p> <p>Results</p> <p>We analyzed macrophage responses to additions of Zymosan A, polystyrene beads (PBs) (benign substances) or SWCNT (3-150 μg/ml) in the QCMB over 18 hrs. In parallel, toxicity was monitored over 24/48 hrs using conventional viability assays and histological stains to detect apoptosis. In the QCMB, a stable unchanging oscillation frequency occurred when cells alone, Zymosan A alone, PBs alone or SWCNTs without cells at the highest dose alone were used. With living cells in the QCMB, when Zymosan A, PBs or SWCNTs were added, a significant decrease in frequency occurred from 1-6 hrs. For SWCNTs, this Δf was dose-dependent. From 6-18 hrs, benign substances or low dose SWCNT (3-30 μg/ml) treatments showed a reversal of the decrease of oscillation frequency, returning to or exceeding pre-treatment levels. Cell recovery was confirmed in conventional assays. The lag time to see the Δf reversal in QCMB plots was linearly SWCNT-dose dependent. Lastly, the frequency never reversed at high dose SWCNT (100-150 μg/ml), and apoptosis/necrosis was documented in conventional 24 and 48 hr-assays.</p> <p>Conclusion</p> <p>These data suggest that the new QCMB detects and provides unique information about peak, sub-lethal and toxic exposures of living cells to ENMs before they are detected using conventional cell assays.</p

Evaluation of cytotoxic, genotoxic and inflammatory responses of nanoparticles from photocopiers in three human cell lines

Background: Photocopiers emit nanoparticles with complex chemical composition. Short-term exposures to modest nanoparticle concentrations triggered upper airway inflammation and oxidative stress in healthy human volunteers in a recent study. To further understand the toxicological properties of copier-emitted nanoparticles, we studied in-vitro their ability to induce cytotoxicity, pro-inflammatory cytokine release, DNA damage, and apoptosis in relevant human cell lines. Methods: Three cell types were used: THP-1, primary human nasal- and small airway epithelial cells. Following collection in a large volume photocopy center, nanoparticles were extracted, dispersed and characterized in the cell culture medium. Cells were doped at 30, 100 and 300 μg/mL administered doses for up to 24 hrs. Estimated dose delivered to cells, was ~10% and 22% of the administered dose at 6 and 24 hrs, respectively. Gene expression analysis of key biomarkers was performed using real time quantitative PCR (RT-qPCR) in THP-1 cells at 5 μg nanoparticles/mL for 6-hr exposure for confirmation purposes. Results: Multiple cytokines, GM-CSF, IL-1β, IL-6, IL-8, IFNγ, MCP-1, TNF-α and VEGF, were significantly elevated in THP-1 cells in a dose-dependent manner. Gene expression analysis confirmed up-regulation of the TNF-α gene in THP-1 cells, consistent with cytokine findings. In both primary epithelial cells, cytokines IL-8, VEGF, EGF, IL-1α, TNF-α, IL-6 and GM-CSF were significantly elevated. Apoptosis was induced in all cell lines in a dose-dependent manner, consistent with the significant up-regulation of key apoptosis-regulating genes P53 and Casp8 in THP-1 cells. No significant DNA damage was found at any concentration with the comet assay. Up-regulation of key DNA damage and repair genes, Ku70 and Rad51, were also observed in THP-1 cells, albeit not statistically significant. Significant up-regulation of the key gene HO1 for oxidative stress, implicates oxidative stress induced by nanoparticles. Conclusions: Copier-emitted nanoparticles induced the release of pro-inflammatory cytokines, apoptosis and modest cytotoxicity but no DNA damage in all three-human cell lines. Taken together with gene expression data in THP-1 cells, we conclude that these nanoparticles are directly responsible for inflammation observed in human volunteers. Further toxicological evaluations of these nanoparticles, including across different toner formulations, are warranted

The Human Disease Ontology 2022 update.

The Human Disease Ontology (DO) (www.disease-ontology.org) database, has significantly expanded the disease content and enhanced our userbase and website since the DO\u27s 2018 Nucleic Acids Research DATABASE issue paper. Conservatively, based on available resource statistics, terms from the DO have been annotated to over 1.5 million biomedical data elements and citations, a 10× increase in the past 5 years. The DO, funded as a NHGRI Genomic Resource, plays a key role in disease knowledge organization, representation, and standardization, serving as a reference framework for multiscale biomedical data integration and analysis across thousands of clinical, biomedical and computational research projects and genomic resources around the world. This update reports on the addition of 1,793 new disease terms, a 14% increase of textual definitions and the integration of 22 137 new SubClassOf axioms defining disease to disease connections representing the DO\u27s complex disease classification. The DO\u27s updated website provides multifaceted etiology searching, enhanced documentation and educational resources

The DO-KB Knowledgebase: a 20-year journey developing the disease open science ecosystem.

In 2003, the Human Disease Ontology (DO, https://disease-ontology.org/) was established at Northwestern University. In the intervening 20 years, the DO has expanded to become a highly-utilized disease knowledge resource. Serving as the nomenclature and classification standard for human diseases, the DO provides a stable, etiology-based structure integrating mechanistic drivers of human disease. Over the past two decades the DO has grown from a collection of clinical vocabularies, into an expertly curated semantic resource of over 11300 common and rare diseases linking disease concepts through more than 37000 vocabulary cross mappings (v2023-08-08). Here, we introduce the recently launched DO Knowledgebase (DO-KB), which expands the DO\u27s representation of the diseaseome and enhances the findability, accessibility, interoperability and reusability (FAIR) of disease data through a new SPARQL service and new Faceted Search Interface. The DO-KB is an integrated data system, built upon the DO\u27s semantic disease knowledge backbone, with resources that expose and connect the DO\u27s semantic knowledge with disease-related data across Open Linked Data resources. This update includes descriptions of efforts to assess the DO\u27s global impact and improvements to data quality and content, with emphasis on changes in the last two years

Harmonizing model organism data in the Alliance of Genome Resources.

The Alliance of Genome Resources (the Alliance) is a combined effort of 7 knowledgebase projects: Saccharomyces Genome Database, WormBase, FlyBase, Mouse Genome Database, the Zebrafish Information Network, Rat Genome Database, and the Gene Ontology Resource. The Alliance seeks to provide several benefits: better service to the various communities served by these projects; a harmonized view of data for all biomedical researchers, bioinformaticians, clinicians, and students; and a more sustainable infrastructure. The Alliance has harmonized cross-organism data to provide useful comparative views of gene function, gene expression, and human disease relevance. The basis of the comparative views is shared calls of orthology relationships and the use of common ontologies. The key types of data are alleles and variants, gene function based on gene ontology annotations, phenotypes, association to human disease, gene expression, protein-protein and genetic interactions, and participation in pathways. The information is presented on uniform gene pages that allow facile summarization of information about each gene in each of the 7 organisms covered (budding yeast, roundworm Caenorhabditis elegans, fruit fly, house mouse, zebrafish, brown rat, and human). The harmonized knowledge is freely available on the alliancegenome.org portal, as downloadable files, and by APIs. We expect other existing and emerging knowledge bases to join in the effort to provide the union of useful data and features that each knowledge base currently provides

The mouse Gene Expression Database (GXD): 2019 update.

The mouse Gene Expression Database (GXD) is an extensive, well-curated community resource freely available at www.informatics.jax.org/expression.shtml. Covering all developmental stages, GXD includes data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments in wild-type and mutant mice. GXD\u27s gene expression information is integrated with the other data in Mouse Genome Informatics and interconnected with other databases, placing these data in the larger biological and biomedical context. Since the last report, the ability of GXD to provide insights into the molecular mechanisms of development and disease has been greatly enhanced by the addition of new data and by the implementation of new web features. These include: improvements to the Differential Gene Expression Data Search, facilitating searches for genes that have been shown to be exclusively expressed in a specified structure and/or developmental stage; an enhanced anatomy browser that now provides access to expression data and phenotype data for a given anatomical structure; direct access to the wild-type gene expression data for the tissues affected in a specific mutant; and a comparison matrix that juxtaposes tissues where a gene is normally expressed against tissues, where mutations in that gene cause abnormalities