Catalytically distinct IDH1 mutants tune phenotype severity in tumor models.

Mutations in isocitrate dehydrogenase 1 (IDH1) impart a neomorphic reaction that produces the oncometabolite D-2-hydroxyglutarate (D2HG), which can inhibit DNA and histone demethylases to drive tumorigenesis via epigenetic changes. Though heterozygous point mutations in patients primarily affect residue R132, there are myriad D2HG-producing mutants that display unique catalytic efficiency of D2HG production. Here, we show that catalytic efficiency of D2HG production is greater in IDH1 R132Q than R132H mutants, and expression of IDH1 R132Q in cellular and mouse xenograft models leads to higher D2HG concentrations in cells, tumors, and sera compared to R132H-expressing models. Reduced representation bisulfite sequencing (RRBS) analysis of xenograft tumors shows expression of IDH1 R132Q relative to R132H leads to hypermethylation patterns in pathways associated with DNA damage. Transcriptome analysis indicates that the IDH1 R132Q mutation has a more aggressive pro-tumor phenotype, with members of EGFR, Wnt, and PI3K signaling pathways differentially expressed, perhaps through non-epigenetic routes. Together, these data suggest that the catalytic efficiency of IDH1 mutants modulate D2HG levels in cellular and in vivo models, resulting in unique epigenetic and transcriptomic consequences where higher D2HG levels appear to be associated with more aggressive tumors.

danRerLib: a Python package for zebrafish transcriptomics.

Summary: Understanding the pathways and biological processes underlying differential gene expression is fundamental for characterizing gene expression changes in response to an experimental condition. Zebrafish, with a transcriptome closely mirroring that of humans, are frequently utilized as a model for human development and disease. However, a challenge arises due to the incomplete annotations of zebrafish pathways and biological processes, with more comprehensive annotations existing in humans. This incompleteness may result in biased functional enrichment findings and loss of knowledge. danRerLib, a versatile Python package for zebrafish transcriptomics researchers, overcomes this challenge and provides a suite of tools to be executed in Python including gene ID mapping, orthology mapping for the zebrafish and human taxonomy, and functional enrichment analysis utilizing the latest updated Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. danRerLib enables functional enrichment analysis for GO and KEGG pathways, even when they lack direct zebrafish annotations through the orthology of human-annotated functional annotations. This approach enables researchers to extend their analysis to a wider range of pathways, elucidating additional mechanisms of interest and greater insight into experimental results. Availability and implementation: danRerLib, along with comprehensive documentation and tutorials, is freely available. The source code is available at https://github.com/sdsucomptox/danrerlib/ with associated documentation and tutorials at https://sdsucomptox.github.io/danrerlib/. The package has been developed with Python 3.9 and is available for installation on the package management systems PIP (https://pypi.org/project/danrerlib/) and Conda (https://anaconda.org/sdsu_comptox/danrerlib) with additional installation instructions on the documentation website.

Development of a Dynamic Network Model to Identify Temporal Patterns of Structural Malformations in Zebrafish Embryos Exposed to a Model Toxicant, Tris(4-chlorophenyl)methanol.

Embryogenesis is a well-coordinated process relying on precise cues and environmental signals that direct spatiotemporal embryonic patterning. Quite often, when one error in this process occurs, others tend to co-occur. We posit that investigating the co-occurrence of these abnormalities over time would yield additional information about the mode of toxicity for chemicals. Here, we use the environmental contaminant tris(4-chlorophenyl)methanol (TCPMOH) as a model toxicant to assess the relationship between exposures and co-occurrence of developmental abnormalities in zebrafish embryos. We propose a dynamic network modeling approach to study the co-occurrence of abnormalities, including pericardial edema, yolk sac edema, cranial malformation, spinal deformity, delayed/failed swim bladder inflation, and mortality induced by TCPMOH exposure. TCPMOH-exposed samples revealed increased abnormality co-occurrence when compared to controls. The abnormalities were represented as nodes in the dynamic network model. Abnormalities with high co-occurrence over time were identified using network centrality scores. We found that the temporal patterns of abnormality co-occurrence varied between exposure groups. In particular, the high TCPMOH exposure group experienced abnormality co-occurrence earlier than the low exposure group. The network model also revealed that pericardial and yolk sac edema are the most common critical nodes among all TCPMOH exposure levels, preceding further abnormalities. Overall, this study introduces a dynamic network model as a tool for assessing developmental toxicology, integrating structural and temporal features with a concentration response.

Mathematical modeling of the interaction between yolk utilization and fish growth in zebrafish, Danio rerio.

Optimal embryonic development plays a major role in the health of an individual beyond the developmental stage. Nutritional perturbation during development is associated with cardiovascular and metabolic disease later in life. With both nutritional uptake and overall growth being risk factors for eventual health, it is necessary to understand not only the behavior of the processes during development but also their interactions. In this study, we used differential equations, image analyses, curve fittings, parameter estimation and laboratory experiments to quantify the rate of yolk absorption and its effect on early development of a vertebrate model (Danio rerio). Findings from this study establish a nonlinear functional relationship between nutrient absorption and early fish growth. We found that the rate of change in fish length and yolk utilization is logistic, that is the yolk decays rapidly for a period of time before leveling out. An interesting finding from this study is that yolk utilization reaches its maximum at 84 h post-fertilization. We validated our mathematical models against experimental observations, making them powerful tools for replication and future simulations.

The ecotoxicological contaminant tris(4-chlorophenyl)methanol (TCPMOH) impacts embryonic development in zebrafish (Danio rerio).

Tris(4-chlorophenyl)methanol (TCPMOH) is a water contaminant with unknown etiology, but is believed to be a byproduct of DDT manufacturing. It is highly persistent in the environment, and bioaccumulates in marine species. TCPMOH has also been measured in human breast milk, which poses a risk for developing infants. However, almost no toxicity data is currently available. In this study, we investigate the hazard posed by developmental TCPMOH exposures using the zebrafish model (Danio rerio). Zebrafish (Danio rerio) embryos were exposed to 0, 0.1, 0.5, 1, or 5 µM TCPMOH beginning at 24 h post fertilization (hpf). Embryonic mortality and incidence of morphological deformities increased in a concentration-dependent manner with TCPMOH exposure. RNA sequencing assessed changes in gene expression associated with acute (4 hour) exposures to 50 nM TCPMOH. Developmental exposure to TCPMOH decreased expression of ahr2, as well as metabolic enzymes cyp1a1, cyp1b1, cyp1c1, cyp1c2, and cyp2y3 (p<0.05). These findings were concordant with decreased Cyp1a1 induction measured by the ethoxyresorufin-O-deethylase (EROD) assay (p<0.05). Pathways associated with xenobiotic metabolism, lipid metabolism, and transcriptional and translational regulation were decreased. Pathways involved in DNA replication and repair, carbohydrate metabolism, and endocrine function were upregulated. Overall, this study demonstrates that TCPMOH is acutely toxic to zebrafish embryos at elevated concentrations.

Acetylcholine Regulates Pulmonary Pathology During Viral Infection and Recovery.

INTRODUCTION: This study was designed to explore the role of acetylcholine (ACh) in pulmonary viral infection and recovery. Inflammatory control is critical to recovery from respiratory viral infection. ACh secreted from non-neuronal sources, including lymphocytes, plays an important, albeit underappreciated, role in regulating immune-mediated inflammation. METHODS: ACh and lymphocyte cholinergic status in the lungs were measured over the course of influenza infection and recovery. The role of ACh was examined by inhibiting ACh synthesis in vivo. Pulmonary inflammation was monitored by Iba1 immunofluorescence, using a novel automated algorithm. Tissue repair was monitored histologically. RESULTS: Pulmonary ACh remained constant through the early stage of infection and increased during the peak of the acquired immune response. As the concentration of ACh increased, cholinergic lymphocytes appeared in the BAL and lungs. Cholinergic capacity was found primarily in CD4 T cells, but also in B cells and CD8 T cells. The cholinergic CD4+ T cells bound to influenza-specific tetramers and were retained in the resident memory regions of the lung up to 2 months after infection. Histologically, cholinergic lymphocytes were found in direct physical contact with activated macrophages throughout the lung. Inflammation was monitored by ionized calcium-binding adapter molecule 1 (Iba1) immunofluorescence, using a novel automated algorithm. When ACh production was inhibited, mice exhibited increased tissue inflammation and delayed recovery. Histologic examination revealed abnormal tissue repair when ACh was limited. CONCLUSION: These findings point to a previously unrecognized role for ACh in the transition from active immunity to recovery and pulmonary repair following respiratory viral infection.