Aptenodytes forsteri
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA384210 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6763800.fastq.gz | Fastqsanger.gz | |||
| SRR6763800_1.fastq.gz | Fastqsanger.gz | |||
| SRR6763800_2.fastq.gz | Fastqsanger.gz | |||
| SRR6763810.fastq.gz | Fastqsanger.gz | |||
| SRR6763810_1.fastq.gz | Fastqsanger.gz |
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Project description:Cytochrome P450 19 (CYP19, aromatase) catalyzes the conversion of androgens to estrogens in a sequence of three reactions that each depend on NADPH and O2. Aromatase is a phylogenetically-ancient enzyme and its breadth of expression in other species has highlighted distinct physiological functions. In songbirds, estrogen production is required for programming the neural circuits controlling song and in the determination of sex in fish and reptiles. This work describes the expression, purification, and biophysical characterization of Aptenodytes forsteri (Emperor penguin, af) aromatase. Using human cytochrome P450 reductase as a redox partner, afCYP19 displayed similar substrate turnover and LC/MS/MS confirmed that afCYP19 catalyzes the transformations through the intermediates 19-hydroxy- and 19-oxo-androstenedione. Androstenedione and anastrozole had the highest affinity for the enzyme and were followed closely by 19-hydroxyandrostenedione and testosterone. The affinity of 19-oxo-androstenedione for afCYP19 was ten-fold lower. The time-dependent changes in the Soret bands observed in stopped-flow mixing experiments of the steroidal ligands and the inhibitor anastrozole with afCYP19 were best described by a two-step binding mechanism. In summary, these studies describe the first biophysical characterization of an avian aromatase that displays strikingly similar enzyme kinetics and ligand binding properties to the human enzyme and could serve as a convenient model system for studies of the enigmatic transformation of androgens to estrogens.
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Project description:Aptenodytes forsteri Genome sequencing and assembly
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Project description:As China's "double carbon" goal continues to advance, logistics as a key area of carbon emissions and low-carbon logistics center site selection are key links in the process. However, existing studies on logistics center location often ignore the impact of demand uncertainty, which leads to a waste of resources in the planning and construction processes. We take logistics cost and carbon emission as the objectives, and the multi-objective site selection model established based on stochastic programming theory takes demand uncertainty as a stochastic constraint. We transform the stochastic constraint model into a 0-1 mixed integer multi-objective planning model by utilizing the idea of equivalence transformation. The Aptenodytes Forsteri Optimization (AFO) algorithm is combined with the Ideal Point Method to solve the model, and the algorithm is compared with the Particle Swarm Optimization (PSO), Differential Evolutionary (DE), Tabu Search (TS), Sparrow Search (SS) algorithms, and the exact solver Linear Interactive and General Optimizer (LINGO). The examples verify the validity of the models and algorithms, with an average reduction of 6.2% and 3.6% in logistics costs and carbon emissions in the case of demand determination, and at the confidence level of 0.9 under demand uncertainty, both logistics costs and carbon emissions are decreased to varying degrees. This study provides a new research idea for the low-carbon logistics location problem under demand uncertainty, which helps to promote the transformation of the logistics industry to low-carbon and high-efficiency.
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Project description:The utility of RADseq in an experimental setting is also demonstrated, based on our chasacterisation of an APOBEC mutation signature in an APOBEC3A transfected mouse cell line. 0D5 cells, derived from SSM3 cells, were co-transfected with a mixture containing pcDNA3.1 vectors expressing either APOBEC3A or APOBEC3B (kindly donated by Vincent Caval), pcDNA3.1 construct expressing deaminase null APOBEC3A linked to a uracil deglycosylase construct and a plasmid encoding mutant GFP and WT mCherry that is a reporter for APOBEC mutagenesis. Cells were grown, and gDNA extracted, prior to preparation of RADseq libraries using a PstI- MspI double-digest. Libraries underwent a Pippin Prep to select fragments in the size range of 220-520 bp (genomic sequence plus 148 bp of adapters). Single-end sequencing (1x101bp) was performed on an Illumina NovaSeq6000 utilizing v1.5 chemistry. Reads were aligned to mm10 using bwa mem and variants called using the GATK4 pipeline.
2023-06-30 | GSE234146 | GEO