Dataset Information

Identification of FgPacC interactor

ABSTRACT: Identification of Transcription factor FgPacC Interacting Protein by LC-MSMS

INSTRUMENT(S): Q Exactive HF-X

ORGANISM(S): Gibberella Zeae (strain Ph-1 / Atcc Mya-4620 / Fgsc 9075 / Nrrl 31084) (wheat Head Blight Fungus) (fusarium Graminearum)

SUBMITTER: Bingqin Yuan

LAB HEAD: Xuewen Gao

PROVIDER: PXD029059 | Pride | 2022-08-11

REPOSITORIES: pride

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Publications

Inhibition of histone acetyltransferase GCN5 by a transcription factor FgPacC controls fungal adaption to host-derived iron stress.

Gu Qin Q Wang Yujie Y Zhao Xiaozhen X Yuan Bingqin B Zhang Mengxuan M Tan Zheng Z Zhang Xinyue X Chen Yun Y Wu Huijun H Luo Yuming Y Keller Nancy P NP Gao Xuewen X Ma Zhonghua Z

Nucleic acids research 20220601 11

Poaceae plants can locally accumulate iron to suppress pathogen infection. It remains unknown how pathogens overcome host-derived iron stress during their successful infections. Here, we report that Fusarium graminearum (Fg), a destructive fungal pathogen of cereal crops, is challenged by host-derived high-iron stress. Fg infection induces host alkalinization, and the pH-dependent transcription factor FgPacC undergoes a proteolytic cleavage into the functional isoform named FgPacC30 under alkali ...[more]

PMID: 35687128

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Project description:Background: With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studies. While probe-design is a major research area, relatively little work has been reported on the optimization of microarray protocols. Results: As shown in this study, suboptimal conditions can have considerable impact on biologically relevant observations. For example, deviation from the optimal temperature by one degree Celsius lead to a loss of 44% of differentially expressed genes identified. While genes from thousands of Gene Ontology categories were affected, transcription factors and other low-copy-number regulators were disproportionately lost. Calibrated protocols are thus required in order to take full advantage of the large dynamic range of microarrays. For an objective optimization of protocols we introduce an approach that maximizes the amount of information obtained per experiment. A comparison of two typical samples is sufficient for this calibration. We ensure, however, that optimization results are independent of the samples and the specific measures used for calibration. Both simulations and spike-in experiments confirm an unbiased determination of generally optimal experimental conditions. Conclusions: Well calibrated hybridization conditions are thus easily achieved and necessary for the efficient detection of differential expression. They are essential for the sensitive profiling of low-copy-number molecules. This is particularly critical for studies of transcription factor expression, or the inference and study of regulatory networks. Supporting material, including source code and data, is available at http://bioinf.boku.ac.at/pub/optMA2010/. Optimization of hybridization temperature via an assessment of differential expression between two samples (male vs female Drosophila melanogaster) in 6 technical replicates (3 regular + 3 dye-swaps) for hybridizations at different temperatures (in two batches of 50, 52, 54, and 56; and 47, 49, 50, and 51 degree Celsius, with the repeated hybridization at 50 degree Celsius serving to demonstrate batch-to-batch stability).

			Action	DRS
	GFP_beeds_IP.dat	Other
	GFP_beeds_IP.raw	Raw
	PacC27_GFP_Beeds_IP-proSummary.txt	Txt
	PacC30_GFP_Beeds_IP.dat	Other
	PacC30_GFP_Beeds_IP.raw	Raw