EDNA water samples from lakes in the Adirondack Park, NY
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1246971 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:2015 eDNA sampling pilot from stream near Cortland, NY, USA Targeted loci environmental
| PRJNA431582 | ENA
Project description:In Staphylococcus aureus, the role of the GGDEF domain containing protein GdpS remains poorly understood. Previous studies reported that gdpS mutant strains had decreased biofilm formation due to changes in icaADBC expression that were independent of cyclic-di-GMP levels. We deleted gdpS in three unrelated S. aureus isolates, and analyzed the resultant mutants for alterations in biofilm formation, metabolism and transcription. Dynamic imaging during biofilm development showed that GdpS inhibited early biofilm formation in only two out of the three strains examined, without affecting bacterial survival. However, quantification of biofilm formation using crystal violet staining revealed that inactivation of gdpS affected biofilm formation in all three studied strains. Extraction of metabolites from S. aureus cells confirmed the absence of cyclic-di-GMP, suggesting that biofilm formation in this species differs from that in other Gram-positive organisms. In addition, targeted mutagenesis demonstrated that the GGDEF domain was not required for GdpS activity. Transcriptomic analysis revealed that the vast majority of GGDEF-regulated genes were involved in virulence, metabolism, cell wall biogenesis and eDNA release. Finally, expression of lrgAB or deletion of cidABC in a strain lacking gdpS confirmed the role of GdpS on regulation of eDNA production that occurred without an increase in cell autolysis. In summary, S. aureus GdpS contributes to cell-to-cell interactions during early biofilm formation by influencing expression of lrgAB and cidABC mediated eDNA release. We conclude that GdpS acts as a negative regulator of eDNA release.
2014-06-30 | GSE48656 | GEO
Project description:Fluoribacter dumoffii NY 23 strain:NY 23 Genome sequencing and assembly
| PRJNA74015 | ENA
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.
2022-12-01 | GSE146903 | GEO
Project description:Hourly time course samples for the no yeast (NY) treatment group. Note that the samples at hours 4 and 8 do not have microarray data due to insufficient RNA yield. Larvae were reared on standard diet until early third instar, at which time they were washed and transferred to standard diet lacking yeast. The animals remained on this diet until four days after emergence, when one group of adults was switched back to standard diet containing yeast (group Y) while another remained on the diet lacking yeast (group NY). Flies from both groups were killed every hour for the next twelve hours, creating 24 samples across the two treatments. In addition, four samples of flies were killed just before the start of the time course and used as baseline replicates for the no yeast (NY) and yeast (Y) treatments. Baseline replicates were temporally ordered as noted for change-point analysis. No yeast (NY) treatment samples at hours four and eight did not yield microarray data due to insufficient RNA. Total RNA was extracted from whole animals using Trizol (Invitrogen). Sample processing and microarray hybridization/scanning were performed at the Brown University Center for Genetics and Genomics according to Affymetrix protocol. Microarray data was normalized by DNA-Chip Analyzer (dChip, http://www.dchip.org), which utilizes an invariant difference selection (IDS) algorithm to construct a normalization relation. Keywords = insulin, diet, nutrition Keywords: time-course
2003-12-19 | GSE547 | GEO
Project description:Assessing seagrass meadows fish diversity using eDNA
| PRJNA777404 | ENA
Project description:In Staphylococcus aureus, the role of the GGDEF domain containing protein GdpS remains poorly understood. Previous studies reported that gdpS mutant strains had decreased biofilm formation due to changes in icaADBC expression that were independent of cyclic-di-GMP levels. We deleted gdpS in three unrelated S. aureus isolates, and analyzed the resultant mutants for alterations in biofilm formation, metabolism and transcription. Dynamic imaging during biofilm development showed that GdpS inhibited early biofilm formation in only two out of the three strains examined, without affecting bacterial survival. However, quantification of biofilm formation using crystal violet staining revealed that inactivation of gdpS affected biofilm formation in all three studied strains. Extraction of metabolites from S. aureus cells confirmed the absence of cyclic-di-GMP, suggesting that biofilm formation in this species differs from that in other Gram-positive organisms. In addition, targeted mutagenesis demonstrated that the GGDEF domain was not required for GdpS activity. Transcriptomic analysis revealed that the vast majority of GGDEF-regulated genes were involved in virulence, metabolism, cell wall biogenesis and eDNA release. Finally, expression of lrgAB or deletion of cidABC in a strain lacking gdpS confirmed the role of GdpS on regulation of eDNA production that occurred without an increase in cell autolysis. In summary, S. aureus GdpS contributes to cell-to-cell interactions during early biofilm formation by influencing expression of lrgAB and cidABC mediated eDNA release. We conclude that GdpS acts as a negative regulator of eDNA release. Three strains UAMS-1, SA113 and SA564 were used in this study to compare wt with gdpS mutant after 5 hours of growth in static conditions (biofilm formation).
2014-06-30 | E-GEOD-48656 | biostudies-arrayexpress
Project description:Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics.
2024-04-14 | E-MTAB-13075 | biostudies-arrayexpress
Project description:eDNA samples from Yangtze River Metagenome
| PRJNA1275651 | ENA
Project description:In this work, we compared the expression profiles of Anti-NY-ESO1- transduced T-cells with Anti-NY-ESO1- transduced T-cells co-cultured with SK-Mel-37.
2023-07-31 | GSE238192 | GEO