The PHO81 gene is thought to encode an inhibitor of the negative regulators (Pho80p and Pho85p) in the phosphatase (PHO) regulon. Transcription of PHO81 is regulated by Pi signals through the same PHO regulatory system. Elimination of the PHO81 promoter or its substitution by the GAL1 promoter revealed that stimulation of the PHO regulatory system requires both increased transcription of PHO81 and a Pi starvation signal. The predicted Pho81p protein contains 1,179 amino acids (aa) and has six repeats of an ankyrin-like sequence in its central region. The minimum amino acid sequence required for Pho81p function was narrowed down to a 141-aa segment (aa 584 to 724), which contains the fifth and sixth repeats of the ankyrin-like motif. The third to sixth repeats of the ankyrin-like motif of Pho81p have significant similarities to that of p16INK4, which inhibits activity of the human cyclin D-CDK4 kinase complex. Deletion analyses revealed that the N- and C-terminal regions of Pho81p behave as negative and positive regulatory domains, respectively, for the minimal 141-aa region. The negative regulatory activity of the N-terminal domain was antagonized by a C-terminal segment of Pho81p supplied in trans. All four known classes of PHO81c mutations that show repressible acid phosphatase activity in high-Pi medium affect the N-terminal half of Pho81p. An in vitro assay showed that a glutathione S-transferase-Pho81p fusion protein inhibits the Pho85p protein kinase. Association of Pho81p with Pho85p or with the Pho80p-Pho85p complex was demonstrated by the two-hybrid system.
The PHO81 gene encoding one of the regulators of the phosphatase regulon in Saccharomyces cerevisiae was mapped 9.8 centimorgans distal from the ser2 locus on the right arm of chromosome VII. Determination of the nucleotide sequence of cloned PHO81 DNA revealed a 3537 bp open reading frame encoding a 134 kDa protein. This protein has six repeats of a 33-amino acid sequence homologous to the ankyrin repeat and an asparagine-rich region. Transcription of PHO81 is activated by Pho4 protein in cooperation with Pho2 (i.e., Bas2/Grf10) protein under the influence of the inorganic phosphate (Pi) concentration in the medium, through the PHO regulatory system. Major transcription initiation sites of PHO81, determined by primer extension analysis, are at nucleotide positions -66 and -65 relative to the ATG codon. Deletion analysis showed that a 95 bp region from nucleotide position -385 to -291 is essential for response to the Pi signals. Purified Pho4 protein protected a 19 bp region (positions -350 to -332) in the 95 bp fragment from DNase I digestion in vitro and the protected region includes the core sequence 5'-CACGTG-3', which is also observed in other genes of phosphate metabolism.
The roles of natriuretic peptides in cardiovascular homeostasis have been well characterized. A recent study revealed that mice lacking natriuretic peptide receptor-C (NPR-C) exhibit skeletal-overgrowth. We therefore, performed in situ hybridization with riboprobes to determine the localization of mRNAs for receptors for natriuretic peptides in the growth plate of the fetal mouse tibia The amount of mRNA for NPR-A was below the detectable level in the growth plate. The mRNA for NPR-B was detected predominantly in proliferating chondrocytes. By contrast, high levels of mRNA for NPR-C were found in hypertrophic chondrocytes. In other regions of the growth plate, the levels of mRNA for NPR-C were very low. The patterns of expression of mRNAs for NPR-B and NPR-C, namely, subtype switching during differentiation from proliferating chondrocytes to hypertrophic chondrocytes, suggest that these receptors might be involved in the growth and differentiation of the growth plate during fetal development in the mouse.
A piecewise constant spiking neuron model is a simple electronic hardware neuron model, which can exhibit various neuronlike behaviors. In this brief, theoretical formulas of nonlinear input-output (I-O) characteristics of the model and corresponding parameter conditions are provided. Then, an efficient parameter search algorithm, which wisely utilizes the theoretical analysis results, is presented. It is shown that the algorithm enables the model to reproduce given nonlinear I-O characteristics of a neuron efficiently. Also, real circuit experiments validate the reproduction of the given characteristics.
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