Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1176268 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31091000_1.fastq.gz | Fastqsanger.gz | |||
| SRR31091000_2.fastq.gz | Fastqsanger.gz | |||
| SRR31091001_1.fastq.gz | Fastqsanger.gz | |||
| SRR31091001_2.fastq.gz | Fastqsanger.gz | |||
| SRR31091002_1.fastq.gz | Fastqsanger.gz |
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Project description:Today, many contaminants of emerging concern can be measured in waters across the United States, including the tributaries of the Great Lakes. However, just because the chemicals can be measured does not mean that they necessarily result in harm to fish and other aquatic species. Complicating risk assessment in these waters is the fact that aquatic species are encountering the chemicals as mixtures, which may have additive or synergistic risks that cannot be calculated using single chemical hazard and concentration-response information. We developed an in vitro effects-based screening approach to help us predict potential liver toxicity and cancer in aquatic organisms using water from specific Great Lakes tributaries: St. Louis River (MN), Bad River (WI), Fox River (WI), Manitowoc River (WI), Milwaukee River (WI), Indiana Harbor Canal (IN), St. Joseph River (MI), Grand River (MI), Clinton River (MI), River Rouge (MI), Maumee River (OH), Vermilion River (OH), Cuyahoga River (OH), Genesee River (NY), and Oswego River (NY). We exposed HepG2 cells for 48hrs to medium spiked with either field collected water (final concentration of environmental samples in the exposure medium were 75% of the field-collected water samples) or purified water. Using a deep neural network we clustered our collection sites from each tributary based on water chemistry. We also performed high throughput transcriptomics on the RNA obtained from the HepG2 cells. We used the transcriptomics data with our Bayesian Inferene for Sustance and Chemical Toxicity (BISCT) Bayesian Network for Steatosis to predict the probability of the field samples yielding a gene expression pattern consistent with predicting steatosis as an outcome. Surprisingly, we found that the probability of steatosis did not correspond to the surface water chemistry clustering. Our analysis suggests that chemical signatures are not informative in predicting biological effects. Furthermore, recent reports published after we obtained our samples, suggest that chemical levels in the sediment may be more relevant for predicting potential biological effects in the fish species developing tumors in the Great Lakes basin.
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Project description:Purpose: The objective of this study was to evaluate the transcriptomic consequence of chronic exposure to deficient and excessive arginine supply in MIN6 pancreatic beta cells and reveal the molecular mechanisms underlying beta cell function and insulin secretion to arginine administration. Methods: After overnight adhesion, the medium was removed, and the cells were incubated in fresh DMEM medium containing low-, standard- or high-arginine concentration (LA, SA and HA) for 24 h. Following the treatment, RNA was extracted from cells for transcriptome sequencing. Results: Transcriptomics analysis allowed the detection of 23,620 and 22,939 transcripts in the LA and HA samples, among which 7,591 (3,736 up- and 3,855 down-regulated) and 197 (111 up- and 86 down-regulated) genes were expressed differently compared with the SA treatment. One hundred and forty one DEGs were overlapped between LA vs. SA and HA vs. SA comparisons, which were mainly involved in DNA replication, organic hydroxy compound metabolism and cellular response to oxidative stress. GO functional enrichment analysis demonstrated that terms related to proteasomal protein catabolic process, mRNA processing and ATP metabolic process were highly disturbed by LA administration, while DEGs induced by HA were mainly enriched to ammonium ion metabolic process, mRNA export and sterol biosynthetic process. Morever, KEGG pathway analysis revealed that DEGs between LA and SA treatments were mainly functionally classified as involved in protein processing in endoplasmic reticulum and oxidative phosphorylation, while DNA replication, steroid biosynthesis and cell cycle had more counts and reached significant difference levels according to the DEGs triggered by HA. Conclusions: These results suggested that the disturbed carbohydrate, lipid and amino acid metabolisms as well as the decreased cell proliferation, increased apoptosis and elevated oxidative stress contributed to the reduced insulin secretion in beta cells induced by LA or HA administrations.
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Project description:To characterize a expression patterns in the heart, we used rat. 12 Wistar male rats (8 - 11 weeks) were sacrificed. Left atrium (LA) adjacent to the pulmonary vein (PV), a mass of left ventricle (LV), and free-wall of the right ventricle (RV) was isolated. Each LV mass was dissected into three pieces as samples. Because the SAN isolation procedure takes approximately 20 minutes, SA was isolated separately. The SA region was delimited by the borders of the crista terminalis, the interatrial septum, the superior vena cava, and right atrium (RA). In addition to PV, LV, RV, SA, and RA samples, pulmonary arteries were added to the samples for the rat microarray.
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Project description:The recently identified histone modification lysine lactylation can be stimulated by L-lactate and glycolysis. Although the chemical group added upon lysine lactylation was originally proposed to be the L-enantiomer of lactate (KL-la), two isomeric modifications, lysine D-lactylation (KD-la), and N-ε-(carboxyethyl) lysine (Kce), also exist in cells, with their precursors being metabolites of glycolysis. The dynamic regulation and differences among these three modifications in response to hypoxia have not been investigated previously. In this study, we demonstrate that intracellular KL-la, but not KD-la or Kce, is upregulated in response to hypoxia. Depletion of glyoxalase enzymes, GLO1 and GLO2, had minimal impact on KD_x001E_la, Kce, or hypoxia-induced KL-la. Conversely, blocking glycolytic flux to L-lactate under hypoxic conditions by knocking out LDHA/B completely abolished the induction of KL-la, but increased KD-la and Kce. We further observed a correlation between the level of KL-la and HIF-1α expression under hypoxic conditions and when small molecules were used to stabilize HIF-1α in the normoxia condition. Our result demonstrated that there is a strong correlation between HIF-1α and KL-la in lung cancer tissues, and that patient samples with higher grade tend to have higher KL-la levels. Using a proteomics approach, we quantified 66 KL-la sites that were upregulated by hypoxia and demonstrated that p300/CBP contributes to hypoxia-induced KL-la. Collectively, our study demonstrates that KL-la, rather than KD-la or Kce, is the prevailing lysine lactylation in response to hypoxia. Our results therefore demonstrate a link between KL-la and the hypoxia-induced adaptation of tumor cells.
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