The C‐degron pathway eliminates mislocalized proteins and products of deubiquitinating enzymes

Protein termini are determinants of protein stability. Proteins bearing degradation signals, or degrons, at their amino‐ or carboxyl‐termini are eliminated by the N‐ or C‐degron pathways, respectively. We aimed to elucidate the function of C‐degron pathways and to unveil how normal proteomes are exempt from C‐degron pathway‐mediated destruction. Our data reveal that C‐degron pathways remove mislocalized cellular proteins and cleavage products of deubiquitinating enzymes. Furthermore, the C‐degron and N‐degron pathways cooperate in protein removal. Proteome analysis revealed a shortfall in normal proteins targeted by C‐degron pathways, but not of defective proteins, suggesting proteolysis‐based immunity as a constraint for protein evolution/selection. Our work highlights the importance of protein termini for protein quality surveillance, and the relationship between the functional proteome and protein degradation pathways.     

CaMV 35S promoter directs β-glucuronidase expression in the laticiferous system of transgenic Hevea brasiliensis (rubber tree)

Hevea brasiliensis anther calli were genetically transformed using Agrobacterium GV2260 (p35SGUSINT) that harboured the β-glucuronidase (gus) and neomycin phosphotransferase (nptII) genes. β-Glucuronidase protein (GUS) was expressed in the leaves of kanamycin-resistant plants that were regnerated, and the presence of the gene was confirmed by Southern analysis. GUS was also observed to be expressed in the latex and more importantly in the serum fraction. Transverse sections of the leaf petiole from a transformed plant revealed GUS expression to be especially enhanced in the phloem and laticifers. GUS expression was subsequently detected in every one of 194 plants representing three successive vegetative cycles propagated from the original transformant. Transgenic Hevea could thus facilitate the continual production of foreign proteins expressed in the latex. Received: 14 February 1997 / Revision received: 16 August 1997 / Accepted: 20 July 1997     

Detecting the Coevolution of Biosequences An Example of RNA Interaction Prediction

Mol. Biol. Evol. 24: 1592–1595. 2007. doi:10.1093/molbev/msm142 The following corrections were not incorporated into the paper: 1) In     

Detecting the coevolution of biosequences--an example of RNA interaction prediction

A probabilistic graphical model is proposed in order to detect the coevolution between different sites in biological sequences. The model extends the continuous-time Markov process of sequence substitution for single nucleic or amino acids and imposes general constraints regarding simultaneous changes on the substitution rate matrix. Given a multiple sequence alignment for each molecule of interest and a phylogenetic tree, the model can predict potential interactions within or between nucleic acids and proteins. Initial validation of the model is carried out using tRNA and 16S rRNA sequence data. The model accurately identifies the secondary interactions of tRNA as well as several known tertiary interactions. In addition, results on 16S rRNA data indicate this general and simple coevolutionary model outperforms several other parametric and nonparametric methods in predicting secondary interactions. Furthermore, the majority of the putative predictions exhibit either direct contact or proximity of the nucleotide pairs in the 3-dimensional structure of the Thermus thermophilus ribosomal small subunit. The results on RNA data suggest a general model of coevolution might be applied to other types of interactions between protein, DNA, and RNA molecules.     

Validation and refinement of gene-regulatory pathways on a network of physical interactions

As genome-scale measurements lead to increasingly complex models of gene regulation, systematic approaches are needed to validate and refine these models. Towards this goal, we describe an automated procedure for prioritizing genetic perturbations in order to discriminate optimally between alternative models of a gene-regulatory network. Using this procedure, we evaluate 38 candidate regulatory networks in yeast and perform four high-priority gene knockout experiments. The refined networks support previously unknown regulatory mechanisms downstream of SOK2 and SWI4.     

The domain responsible for sphingomyelin synthase (SMS) activity

Sphingomyelin synthase (SMS) sits at the crossroads of sphingomyelin (SM), ceramide, diacylglycerol (DAG) metabolism. It utilizes ceramide and phosphatidylcholine as substrates to produce SM and DAG, thereby regulating lipid messengers which play a role in cell survival and apoptosis. There are two isoforms of the enzyme, SMS1 and SMS2. Both SMS1 and SMS2 contain two histidines and one aspartic acid which are evolutionary conserved within the lipid phosphate phosphatase superfamily. In this study, we systematically mutated these amino acids using site-directed mutagenesis and found that each point mutation abolished SMS activity without altering cellular distribution. We also explored the domains which are responsible for cellular distribution of both enzymes. Given their role as a potential regulator of diseases, these findings, coupled with homology modeling of SMS1 and SMS2, will be useful for drug development targeting SMS.     

Prostaglandins, not cyclic GMP, inhibit oxytocinase isoenzymes from human amniotic fluid in vitro

Two isoenzymes of oxytocinase (EC 3.4.11.3) activity were fractionated from human amniotic fluid samples between the 14th and 22nd weeks of gestation by Ultrogel acrylamide-agarose gel filtration and partially characterized. The isoenzymes were competitively inhibited by PGE₁, PGE₂ and PGF_2α more at pH 6.2 than at pH 6.8, whereas cyclic GMP (cGMP) and its 8-bromo derivative had no effect at either pH. The implications of these findings are discussed and it is suggested that since the activity of amniotic fluid oxytocinases is very low or minimal at or near term, inhibition of these by prostaglandins may not have physiological significance in the initiation of human parturition.     

A joint model of regulatory and metabolic networks

Background  

Gene regulation and metabolic reactions are two primary activities of life. Although many works have been dedicated to study each system, the coupling between them is less well understood. To bridge this gap, we propose a joint model of gene regulation and metabolic reactions.