The downregulation of the aflatoxin cluster at higher temperatures may be explained by the BAY 80-6946 nmr low levels of AflR as well as by inhibitor binding due to reduced levels of AflS. This is in contrast to previous microarray studies (OBrian et al., 2007), which reported that the aflR and aflS transcripts were expressed at about the same level under both temperature conditions. This discrepancy may be due to the lower sensitivity
associated with microarray gene expression studies. Unlike the aflatoxin cluster, cluster #55, which controls the biosynthesis of CPA (Chang et al., 2009), was expressed under both conditions, although the expression levels were much higher at the lower temperature (Table 2). This indicates that the two adjacent clusters are regulated by slightly different mechanisms. No putative transcription factor genes have been found in this cluster. CPA is typically produced under the same conditions that favor aflatoxin production. CPA is known to be produced at both high and low growth temperatures, although the 24-h time point may not be its peak production time. Further studies with multiple time points may be needed to elucidate the mechanism of transcriptional regulation of this cluster. Traditionally, researchers relied on microarray technology to
reveal genes required for toxin biosynthesis and regulation in Aspergillus species (OBrian et al., 2007; Wilkinson et al., 2007a, b). However, due to the sensitivity Astemizole problem, Metabolisms tumor microarrays are not the best technology to detect expression levels of regulatory genes, such as aflR and aflS. This study demonstrates that the RNA-Seq approach can profile a cell’s entire transcriptome with almost infinite resolution. The obtained data defined conclusively the complete aflatoxin cluster consisting of 30 genes, which are coordinately regulated. Having the accurate measurement of the aflR and aflS transcript abundance levels allowed us to conclude that high temperature negatively affects aflatoxin production by turning
down transcription of aflR and aflS. We would like to thank Yan Yu, Sana Scherbakova and Karen Beeson from JCVI for their superb technical assistance during library preparation and sequencing. J.Y. and N.D.F. contributed equally to this work. Table S1. Illumina read statistics. Table S2. Gene expression of the 55 predicted secondary metabolism gene clusters in Aspergillus flavus at temperature 30 vs. 37°C. Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article. “
“Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) represents a simple reliable approach for rapid bacterial identification based on specific peptide/protein fingerprints.
- A third cluster contained MHC class I genes and genes related to
- Cluster 4 contained 120 attributes down regulated in any respect
- An alternative approach to cluster validation is to perform clust
- BIBR 1532 321674-73-1 only these isoforms are modulating 2C AR temperature dependent trafficking.
- This cluster was adjacent to, but did not overlap, the right SFG